Developing an ABM-driven Decision Support System in the Emergency Services

Stephen Dobson; M. Burkett; D. Breslin; D. Romano

doi:10.5220/0005773501510157

Developing an ABM-driven Decision Support System in the Emergency Services

Stephen Dobson, M. Burkett, D. Breslin, D. Romano

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding

Abstract

The research presented here outlines an application of Agent-Based Modelling (ABM) used to support strategic decision-making in the emergency services. Here the resulting ABM-driven Decision Support System (DSS) (called ‘Premonition’) is designed to help practitioners engage with a complex and dynamic environment of co-evolving fire risk behaviours through time. Social change is presented here as a process by which behaviours co-evolve within connected networks of agents. ABM is identified as a beneficial approach to simulate changing household behaviours and the influence of social networks, environmental factors, and also fire service interventions within the Sheffield City region, UK. This project seeks to develop a DSS which supports the stages of ‘intelligence’, ‘design’, and ‘choice’ as the decision-maker moves from identifying problem areas, establishing possible strategies for intervention, and predicting possible outcomes of alternative courses of action.

Original language	English
Title of host publication	ICEIS 2016 - Proceedings of the 18th International Conference on Enterprise Information Systems
Editors	S. Hammoudi, L. Maciaszek, M.M. Missikoff, O. Camp, J. Cordeiro
Publisher	SciTePress
Pages	151-157
Volume	2
ISBN (Print)	978-989758187-8
DOIs	https://doi.org/10.5220/0005773501510157
Publication status	Published - 2016
Event	International Conference on Enterprise Information Systems - Rome, Italy Duration: 25 Apr 2016 → 28 Apr 2016

Conference

Conference	International Conference on Enterprise Information Systems
Abbreviated title	ICEIS 2016
Country/Territory	Italy
City	Rome
Period	25/04/16 → 28/04/16

Bibliographical note

The full text is not available on the repository.

Keywords

Decision Support System
Co-evolution
Connectivity
Agent-Based Model
Domestic Fire Risk Behaviour

Access to Document

10.5220/0005773501510157

Cite this

Dobson, S., Burkett, M., Breslin, D., & Romano, D. (2016). Developing an ABM-driven Decision Support System in the Emergency Services. In S. Hammoudi, L. Maciaszek, M. M. Missikoff, O. Camp, & J. Cordeiro (Eds.), ICEIS 2016 - Proceedings of the 18th International Conference on Enterprise Information Systems (Vol. 2, pp. 151-157). SciTePress. https://doi.org/10.5220/0005773501510157

Developing an ABM-driven Decision Support System in the Emergency Services. / Dobson, Stephen; Burkett, M.; Breslin, D. et al.
ICEIS 2016 - Proceedings of the 18th International Conference on Enterprise Information Systems. ed. / S. Hammoudi; L. Maciaszek; M.M. Missikoff; O. Camp; J. Cordeiro. Vol. 2 SciTePress, 2016. p. 151-157.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding

Dobson, S, Burkett, M, Breslin, D & Romano, D 2016, Developing an ABM-driven Decision Support System in the Emergency Services. in S Hammoudi, L Maciaszek, MM Missikoff, O Camp & J Cordeiro (eds), ICEIS 2016 - Proceedings of the 18th International Conference on Enterprise Information Systems. vol. 2, SciTePress, pp. 151-157, International Conference on Enterprise Information Systems, Rome, Italy, 25/04/16. https://doi.org/10.5220/0005773501510157

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keywords = "Decision Support System, Co-evolution, Connectivity, Agent-Based Model, Domestic Fire Risk Behaviour",

author = "Stephen Dobson and M. Burkett and D. Breslin and D. Romano",

note = "The full text is not available on the repository.; International Conference on Enterprise Information Systems, ICEIS 2016 ; Conference date: 25-04-2016 Through 28-04-2016",

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AB - The research presented here outlines an application of Agent-Based Modelling (ABM) used to support strategic decision-making in the emergency services. Here the resulting ABM-driven Decision Support System (DSS) (called ‘Premonition’) is designed to help practitioners engage with a complex and dynamic environment of co-evolving fire risk behaviours through time. Social change is presented here as a process by which behaviours co-evolve within connected networks of agents. ABM is identified as a beneficial approach to simulate changing household behaviours and the influence of social networks, environmental factors, and also fire service interventions within the Sheffield City region, UK. This project seeks to develop a DSS which supports the stages of ‘intelligence’, ‘design’, and ‘choice’ as the decision-maker moves from identifying problem areas, establishing possible strategies for intervention, and predicting possible outcomes of alternative courses of action.

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Developing an ABM-driven Decision Support System in the Emergency Services

Abstract

Conference

Bibliographical note

Keywords

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Cite this